Regression & Linear Models

Case Study: JMP060* Nonlinear Regression Modeling for Cell Growth OptimizationApply nonlinear models to understand the impact of factors on a cell growth.
Case Study: JMP056* Where Have All the Butterflies Gone?Apply time series forecasting and Generalized linear mixed model (GLMM) to evaluate butterfly populations being impacted by climate and land-use changes.
Case Study: JMP035 Durability of Mobile Phone Screen - Part 4Evaluate the durability of mobile phone screens in a drop test across various heights by building a single multiple logistic regression model. Use the model to estimate the probability of a screen being damaged across any drop height.
Case Study: JMP027 Titanic PassengersUse the passenger data related to the sinking of the RMS Titanic ship to explore some questions of interest about survival rates for the Titanic. For example, were there some key characteristics of the survivors? Were some passenger groups more likely to survive than others? Can we accurately predict survival?
Case Study: JMP026 Lost SalesDetermine whether certain conditions make it more likely that a customer order will be won or lost.
Case Study: JMP025 Bank RevenueA bank wants to understand how customer banking habits contribute to revenues and profitability. Build a model that allows the bank to predict profitability for a given customer. The resulting model will be used to forecast bank revenues and guide the bank in future marketing campaigns.
Case Study: JMP024 Housing PricesAfter determining which factors relate to the selling prices of homes located in and around a ski resort, develop a model to predict housing prices.
Case Study: JMP023 Cell Phone ServiceDetermine whether wind speed and barometric pressure are related to phone call performance (percentage of dropped or failed calls) and use the resulting model to predict the percentage of bad calls based upon the weather conditions.

* This case study requires JMP Pro or JMP Student Edition.